Process monitoring and fault detection on a hot-melt extrusion process using in-line Raman spectroscopy and a hybrid soft sensor

Tahir, Furqan and Islam, Muhammad T. and Mack, John and Robertson, John and Lovett, David (2019) Process monitoring and fault detection on a hot-melt extrusion process using in-line Raman spectroscopy and a hybrid soft sensor. Computers and Chemical Engineering, 125. pp. 400-414. ISSN 0098-1354 (https://doi.org/10.1016/j.compchemeng.2019.03.019)

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Abstract

We propose a real-time process monitoring and fault detection scheme for a pharmaceutical hot-melt extrusion process producing Paracetamol-Affinisol extrudate. The scheme involves prediction of Paracetamol concentration from two independent sources: a hybrid soft sensor and a Raman-based Partial Least Squares (PLS) calibration model. Both these predictions are used by the developed PCA (Principal Component Analysis) and SPC (Statistical Process Control) monitors to detect process faults and raise alarms. Through real-time extrusion results, it is shown that this two-sensor approach enables the detection of various common process faults which would otherwise remain undetected with a single-sensor monitoring scheme.

ORCID iDs

Tahir, Furqan, Islam, Muhammad T. ORCID logoORCID: https://orcid.org/0000-0002-3530-0519, Mack, John, Robertson, John ORCID logoORCID: https://orcid.org/0000-0002-2191-1319 and Lovett, David;
CORE (COnnecting REpositories)